Suppr超能文献

细胞集体迁移的多细胞物流。

Multi-cellular logistics of collective cell migration.

机构信息

Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Nara, Japan.

出版信息

PLoS One. 2011;6(12):e27950. doi: 10.1371/journal.pone.0027950. Epub 2011 Dec 21.

Abstract

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes "collective migration," whereas strong noise from non-migratory cells causes "dispersive migration." Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems.

摘要

在发育过程中,生物网络(如器官和神经元网络)的形成受到基于细胞迁移的多细胞运输现象的控制。在多细胞系统中,细胞的运动受到与拥挤空间中其他细胞的物理相互作用的限制,类似于乘客在拥挤的火车上推开其他人。单个细胞的运动本质上是随机的,可以看作是一种随机漫步。然而,由于细胞与随机移动的邻居相互作用,这种行走发生在嘈杂的环境中。尽管存在这种随机性和复杂性,但发育过程高度协调和精确调控,遵循遗传(甚至表观遗传)蓝图。尽管个体细胞迁移已经研究了很长时间,但随机因素如何影响发育过程中精确控制的多细胞运输方式在很大程度上仍然未知。为了探索多细胞迁移的一般原理,我们专注于神经嵴细胞的迁移,这些细胞集体迁移并形成流。我们引入了一个多细胞迁移的力学模型。基于该模型的模拟表明,迁移模式取决于迁移细胞和非迁移细胞的噪声相对强度。迁移细胞的强噪声和周围细胞的弱噪声导致“集体迁移”,而非迁移细胞的强噪声导致“弥散迁移”。此外,我们的理论分析表明,即使没有直接的机械接触,迁移细胞也会在长距离上相互吸引。这种有效相互作用取决于迁移细胞和非迁移细胞的随机性。基于这些发现,我们提出单细胞水平的随机行为可以有效地、精确地实现多细胞系统中的集体迁移。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验